A personalised recommender system for tourists on city trips: concepts and implementation

In this paper we introduce a new recommender system for urban tourists. The goal of the system is to enrich tourists’ experience by offering them personalised tour recommendations tailored to their dynamic user profiles. Particular attention in the proposed approach is paid to the influence of basic leisure needs of an individual, which include new experiences, entertainment, being in open area, relaxation, physical exercise, and socialising, on the tour composition. These needs tend to be dynamic and give rise to saturation effects and variety seeking behaviour. The system is developed as part of the larger c-Space framework, in which a number of technologies, such as projective augmented reality, a newly proposed near real-time 4D dynamic scene reconstruction, and affective computing, are brought together and used to enrich experiences of users in their interactions with built environments. The paper describes the main concepts of the recommender system and its implementation in the specified context of the city of Trento, Italy.